SoroushVahidi/scidocs huggingface dataset:
Multi-Prediction Deep Boltzmann Machines
(2013)

We introduce the multi-prediction deep Boltzmann machine (MP-DBM). The MPDBM can be seen as a single probabilistic model trained to maximize a variational approximation to the generalized pseudolikelihood, or as a family of recurrent nets that share parameters and approximately solve different inference problems. Prior methods of training DBMs either do not perform well on classification tasks or require an initial learning pass that trains the DBM greedily, one layer at a time. The MP-DBM does not require greedy layerwise pretraining, and outperforms the standard DBM at classification, classification with missing inputs, and mean field prediction tasks.1
A Modified CFOA and Its Applications to Simulated Inductors, Capacitance Multipliers, and Analog Filters
(2008)

In this paper, using a minimum number of passive components, i.e., new grounded and floating inductance simulators, grounded capacitance multipliers, and frequency-dependent negative resistors (FDNRs) based on one/two modified current-feedback operational amplifiers (MCFOAs), are proposed. The type of the simulators depends on the passive element selection used in the structure of the circuit without requiring critical active and passive component-matching conditions and/or cancellation constraints. In order to show the flexibility of the proposed MCFOA, a single-input three-output (SITO) voltage-mode (VM) filter, two three-input single-output (TISO) VM filters, and an SITO current-mode (CM) filter employing a single MCFOA are reported. The layout of the proposed MCFOA is also given. A number of simulations using the SPICE program and some experimental tests are performed to exhibit the performance of the introduced structures.
Data Structures for Traveling Salesmen
(1993)

The choice of data structure for tour representation plays a critical role in the efficiency of local improvement heuristics for the Traveling Salesman Problem. The tour data structure must permit queries about the relative order of cities in the current tour and must allow sections of the tour to be reversed. The traditional array-based representation of a tour permits the relative order of cities to be determined in small constant time, but requires worst-case Ω(N) time (where N is the number of cities) to implement a reversal, which renders it impractical for large instances. This paper considers alternative tour data structures, examining them from both a theoretical and experimental point of view. The first alternative we consider is a data structure based on splay trees, where all queries and updates take amortized time O( logN). We show that this is close to the best possible, because in the cell probe model of computation any data structure must take worst-case amortized time Ω( logN /log logN) per operation. Empirically (for random Euclidean instances), splay trees overcome their large constant-factor overhead and catch up to arrays by N = 10 , 000, pulling ahead by a factor of 4-10 (depending on machine) when N = 100 , 000. Two alternative tree-based data structures do even better in this range, however. Although both are asymptotically inferior to the splay tree representation, the latter does not appear to pull even with them until N ∼ 1 , 000 , 000. ________________ 1 Rutgers University, New Brunswick, NJ 08903, and University of California at San Diego, La Jolla, CA 92093 2 Room 2D-150, AT&T Bell Laboratories, Murray Hill, NJ 07974 3 Department of Mathematics and Computer Science, Amherst College, Amherst, MA 01002 4 Department of Mathematics, Rutgers University, New Brunswick, NJ 08903 * A preliminary version of this paper appeared under the same title in Proceedings 4th Ann. ACM-SIAM Symp. on Discrete Algorithms (1993), 145-154.
An Operating System for the Home
(2012)

Network devices for the home such as remotely controllable locks, lights, thermostats, cameras, and motion sensors are now readily available and inexpensive. In theory, this enables scenarios like remotely monitoring cameras from a smartphone or customizing climate control based on occupancy patterns. However, in practice today, such smarthome scenarios are limited to expert hobbyists and the rich because of the high overhead of managing and extending current technology. We present HomeOS, a platform that bridges this gap by presenting users and developers with a PC-like abstraction for technology in the home. It presents network devices as peripherals with abstract interfaces, enables cross-device tasks via applications written against these interfaces, and gives users a management interface designed for the home environment. HomeOS already has tens of applications and supports a wide range of devices. It has been running in 12 real homes for 4–8 months, and 42 students have built new applications and added support for additional devices independent of our efforts.
How do training and competition workloads relate to injury? The workload-injury aetiology model.
(2017)

Injury aetiology models that have evolved over the previous two decades highlight a number of factors which contribute to the causal mechanisms for athletic injuries. These models highlight the pathway to injury, including (1) internal risk factors (eg, age, neuromuscular control) which predispose athletes to injury, (2) exposure to external risk factors (eg, playing surface, equipment), and finally (3) an inciting event, wherein biomechanical breakdown and injury occurs. The most recent aetiological model proposed in 2007 was the first to detail the dynamic nature of injury risk, whereby participation may or may not result in injury, and participation itself alters injury risk through adaptation. However, although training and competition workloads are strongly associated with injury, existing aetiology models neither include them nor provide an explanation for how workloads alter injury risk. Therefore, we propose an updated injury aetiology model which includes the effects of workloads. Within this model, internal risk factors are differentiated into modifiable and non-modifiable factors, and workloads contribute to injury in three ways: (1) exposure to external risk factors and potential inciting events, (2) fatigue, or negative physiological effects, and (3) fitness, or positive physiological adaptations. Exposure is determined solely by total load, while positive and negative adaptations are controlled both by total workloads, as well as changes in load (eg, the acute:chronic workload ratio). Finally, we describe how this model explains the load-injury relationships for total workloads, acute:chronic workload ratios and the training load-injury paradox.
Comparing and Aligning Process Representations
(2018)

Processes within organizations can be highly complex chains of inter-related steps, involving numerous stakeholders and information systems. Due to this complexity, having access to the right information is vital to the proper execution and effective management of an organization’s business processes. A major challenge in this regard is that information on a single process is often spread out over numerous models, documents, and systems. This phenomenon results from efforts to provide a variety of process stakeholders with the information that is relevant to them, in a suitable format. However, this disintegration of process information also has considerable disadvantages for organizations. In particular, it can lead to severe maintenance issues, reduced execution efficiency, and negative effects on the quality of process results. Against this background, this doctoral thesis focuses on the spread of process information in organizations and, in particular, on the mitigation of the negative aspects associated with this phenomenon. The main contributions of this thesis are five techniques that focus on the alignment and comparison of process information from different informational artifacts. Each of these techniques tackles a specific scenario involving multiple informational artifacts that contain process information in different representation formats. Among others, we present automated techniques for the detection of inconsistencies between process models and textual process descriptions, the alignment of process performance measurements to process models, conformance-checking in the context of uncertainty, and the matching of process models through the analysis of event-log information. We demonstrate the efficacy and usefulness of these techniques through quantitative evaluations involving data obtained from real-world settings. Altogether, the presented work provides important contributions for the analysis, comparison, and alignment of process information in various representation formats through the development of novel concepts and techniques. The contributions, furthermore, provide a means for organizations to improve the efficiency and quality of their processes.
Variability of Worked Examples and Transfer of Geometrical Problem-Solving Skills : A Cognitive-Load Approach
(2004)

Four computer-based training strategies for geometrical problem solving in the domain of computer numerically controlled machinery programming were studied with regard to their effects on training performance, transfer performance, and cognitive load. A lowand a high-variability conventional condition, in which conventional practice problems had to be solved (followed by worked examples), were compared with a lowand a high-variability worked condition, in which worked examples had to be studied. Results showed that students who studied worked examples gained most from high-variability examples, invested less time and mental effort in practice, and attained better and less effort-demanding transfer performance than students who first attempted to solve conventional problems and then studied work examples.
Alzheimer's disease: genes, proteins, and therapy.
(2001)

Rapid progress in deciphering the biological mechanism of Alzheimer's disease (AD) has arisen from the application of molecular and cell biology to this complex disorder of the limbic and association cortices. In turn, new insights into fundamental aspects of protein biology have resulted from research on the disease. This beneficial interplay between basic and applied cell biology is well illustrated by advances in understanding the genotype-to-phenotype relationships of familial Alzheimer's disease. All four genes definitively linked to inherited forms of the disease to date have been shown to increase the production and/or deposition of amyloid beta-protein in the brain. In particular, evidence that the presenilin proteins, mutations in which cause the most aggressive form of inherited AD, lead to altered intramembranous cleavage of the beta-amyloid precursor protein by the protease called gamma-secretase has spurred progress toward novel therapeutics. The finding that presenilin itself may be the long-sought gamma-secretase, coupled with the recent identification of beta-secretase, has provided discrete biochemical targets for drug screening and development. Alternate and novel strategies for inhibiting the early mechanism of the disease are also emerging. The progress reviewed here, coupled with better ability to diagnose the disease early, bode well for the successful development of therapeutic and preventative drugs for this major public health problem.
FA*IR: A Fair Top-k Ranking Algorithm
(2017)

In this work, we define and solve the Fair Top-k Ranking problem, in which we want to determine a subset of k candidates from a large pool of n » k candidates, maximizing utility (i.e., select the "best" candidates) subject to group fairness criteria.
 Our ranked group fairness definition extends group fairness using the standard notion of protected groups and is based on ensuring that the proportion of protected candidates in every prefix of the top-k ranking remains statistically above or indistinguishable from a given minimum. Utility is operationalized in two ways: (i) every candidate included in the top-k should be more qualified than every candidate not included; and (ii) for every pair of candidates in the top-k, the more qualified candidate should be ranked above.
 An efficient algorithm is presented for producing the Fair Top-k Ranking, and tested experimentally on existing datasets as well as new datasets released with this paper, showing that our approach yields small distortions with respect to rankings that maximize utility without considering fairness criteria. To the best of our knowledge, this is the first algorithm grounded in statistical tests that can mitigate biases in the representation of an under-represented group along a ranked list.
Lower limb rehabilitation robot
(2009)

This paper describes a new prototype of lower limb rehabilitation robot (for short: LLRR), including its detailed structure, operative principles, manipulative manual and control mode which give considerate protection to patients. It implements the programmable process during the course of the limbs rehabilitation, furthermore, renders variable and predetermined step posture and force sensing. LLRR could assist patient in-- simulating normal people's footsteps, exercising leg muscles, gradually recovering the neural control toward walking function and finally walking in normal way utterly. Such robot is comprised with steps posture controlling system and weight alleviation controlling mechanism.
The Air Traffic Flow Management Problem: An Integer Optimization Approach
(2008)

In this paper, we present a new Integer Program (IP) for the Air Traffic Flow Management (ATFM) problem. The model we propose provides a complete representation of all the phases of each flights, i.e., the phase of taking-off, of cruising and of landing; suggesting all the actions to be implemented to achieve the goal of safe, efficient, and expeditious aircraft movement. The distinctive feature of the model is that it allows rerouting decisions. These decisions are formulated by means of “local” conditions, which allow us to represent such decisions in a very compact way by only introducing new constraints. Moreover, to strengthen the polyhedral structure of the underlying relaxation, we also present three classes of valid inequalities. We report short computational times (less than 15 minutes) on instances of the size of the US air traffic control system that make it realistic that our approach can be used as the main engine of managing air traffic in the US.
An Improved Neural Segmentation Method Based on U-NET
(2017)

摘要:局部麻醉技术作为现代社会最为常见的麻醉技 术,具有安全性高,副作用小等优势。通过分析超声 图像,分割图像中的神经区域,有助于提升局部麻醉 手术的成功率。卷积神经网络作为目前最为高效的图 像处理方法之一,具有准确性高,预处理少等优势。 通过卷积神经网络来对超声图像中的神经区域进行分 割,速度更快,准确性更高。目前已有的图像分割网 络结构主要有U-NET[1],SegNet[2]。U-NET网络训练 时间短,训练参数较少,但深度略有不足。SegNet 网 络层次较深,训练时间过长,但对训练样本需求较多 由于医学样本数量有限,会对模型训练产生一定影响。 本文我们将采用一种改进后的 U-NET 网络结构来对超 声图像中的神经区域进行分割,改进后的 U-NET 网络 结构加入的残差网络(residual network)[3],并对每一层 结果进行规范化(batch normalization)处理[4]。实验结 果表明,与传统的U-NET网络结构相比,改进后的UNET 网络分割效果具有显著提升,训练时间略有增加。 同时,将改进后的 U-NET 网络与 SegNet 网络结构进 行对比,发现改进后的 U-net 无论从训练速度还是从 分割效果均高于 SegNet 网络结构。改进后的 U-net 网 络结构在神经识别方面具有很好的应用场景。
Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels
(2013)

Covariate shift is an unconventional learning scenario in which training and testing data have different distributions. A general principle to solve the problem is to make the training data distribution similar to that of the test domain, such that classifiers computed on the former generalize well to the latter. Current approaches typically target on sample distributions in the input space, however, for kernel-based learning methods, the algorithm performance depends directly on the geometry of the kernel-induced feature space. Motivated by this, we propose to match data distributions in the Hilbert space, which, given a pre-defined empirical kernel map, can be formulated as aligning kernel matrices across domains. In particular, to evaluate similarity of kernel matrices defined on arbitrarily different samples, the novel concept of surrogate kernel is introduced based on the Mercer’s theorem. Our approach caters the model adaptation specifically to kernel-based learning mechanism, and demonstrates promising results on several real-world applications. Proceedings of the 30 th International Conference on Machine Learning, Atlanta, Georgia, USA, 2013. JMLR: W&CP volume 28. Copyright 2013 by the author(s).
Massive Social Network Analysis: Mining Twitter for Social Good
(2010)

Social networks produce an enormous quantity of data. Facebook consists of over 400 million active users sharing over 5 billion pieces of information each month. Analyzing this vast quantity of unstructured data presents challenges for software and hardware. We present GraphCT, a Graph Characterization Toolkit for massive graphs representing social network data. On a 128-processor Cray XMT, GraphCT estimates the betweenness centrality of an artificially generated (R-MAT) 537 million vertex, 8.6 billion edge graph in 55 minutes and a real-world graph (Kwak, et al.) with 61.6 million vertices and 1.47 billion edges in 105 minutes. We use GraphCT to analyze public data from Twitter, a microblogging network. Twitter's message connections appear primarily tree-structured as a news dissemination system. Within the public data, however, are clusters of conversations. Using GraphCT, we can rank actors within these conversations and help analysts focus attention on a much smaller data subset.
Automotive Safety and Security Integration Challenges
(2014)

The ever increasing complexity of automotive vehicular systems, their connection to external networks, to the internet of things as well as their greater internal networking opens doors to hacking and malicious attacks. Security an d privacy risks in modern automotive vehicular systems are well publicized by now. That violation of securit y could lead to safety violations – is a well-argued and accepted argument. The safety discipline has matured over decades , but the security discipline is much younger . There are arguments and rightfully so, that the security engineering process is similar to the functional safety engineering process (formalized by the norm ISO 26262 ) and that they could be laid side -by-side and could be performed together but, by a different set of experts. There are moves to define a security engineering process along the lines of a functional safety engineering process for automotive vehicular systems . But, are these efforts at formalizing safety-security sufficient to produce safe and secure systems? When one sets out on this path with the idea of building safe and s ecure systems , one realizes that there are quite a few challenges, contradictions , dis imilarities, concerns to be addressed before safe and secure systems started coming out of production lines. The effort of this paper is to bring some such challeng e areas to the notice of the community and to suggest a way forward.
Comprehensive Experimental Analyses of Automotive Attack Surfaces
(2011)

Modern automobiles are pervasively computerized, and hence potentially vulnerable to attack. However, while previous research has shown that the internal networks within some modern cars are insecure, the associated threat model — requiring prior physical access — has justifiably been viewed as unrealistic. Thus, it remains an open question if automobiles can also be susceptible to remote compromise. Our work seeks to put this question to rest by systematically analyzing the external attack surface of a modern automobile. We discover that remote exploitation is feasible via a broad range of attack vectors (including mechanics tools, CD players, Bluetooth and cellular radio), and further, that wireless communications channels allow long distance vehicle control, location tracking, in-cabin audio exfiltration and theft. Finally, we discuss the structural characteristics of the automotive ecosystem that give rise to such problems and highlight the practical challenges in mitigating them.
Security Threats to Automotive CAN Networks - Practical Examples and Selected Short-Term Countermeasures
(2008)

The IT security of automotive systems is an evolving area of research. To analyse the current situation and the potentially growing tendency of arising threats we performed several practical tests on recent automotive technology. With a focus on automotive systems based on CAN bus technology, this article summarises the results of four selected tests performed on the control systems for the window lift, warning light and airbag control system as well as the central gateway. These results are supplemented in this article by a classification of these four attack scenarios using the established CERT taxonomy and an analysis of underlying security vulnerabilities, and especially, potential safety implications. With respect to the results of these tests, in this article we further discuss two selected countermeasures to address basic weaknesses exploited in our tests. These are adaptations of intrusion detection (discussing three exemplary detection patterns) and IT-forensic measures (proposing proactive measures based on a forensic model). This article discusses both looking at the four attack scenarios introduced before, covering their capabilities and restrictions. While these reactive approaches are short-term measures, which could already be added to today’s automotive IT architecture, long-term concepts also are shortly introduced, which are mainly preventive but will require a major redesign. Beneath a short overview on respective research approaches, we discuss their individual requirements, potential and restrictions. & 2010 Elsevier Ltd. All rights reserved.
Automatic SQL-to-NoSQL schema transformation over the MySQL and HBase databases
(2015)

The explosive growth of huge data lets cloud computing be more and more popular in recent years. Traditional web-based content management systems (CMS), e.g., phpBB, WordPress, and Joomla, store data using relational databases whose key advantage is the strong relationships among tables. However, regarding the flexibility and the feasibility of parallel processing, cloud computing adopts NoSQL databases that can support horizontal scaling to handle big data. Therefore, how to transform the existing SQL data into the NoSQL database becomes an emerging and necessary issue. This paper is motivated to propose an automatic SQL-to-NoSQL schema transformation mechanism over the MySQL and HBase databases. Based on our experimental results, the proposed mechanism is able to improve about 47% access performance.
Adaptive web search based on user profile constructed without any effort from users
(2004)

Web search engines help users find useful information on the World Wide Web (WWW). However, when the same query is submitted by different users, typical search engines return the same result regardless of who submitted the query. Generally, each user has different information needs for his/her query. Therefore, the search result should be adapted to users with different information needs. In this paper, we first propose several approaches to adapting search results according to each user's need for relevant information without any user effort, and then verify the effectiveness of our proposed approaches. Experimental results show that search systems that adapt to each user's preferences can be achieved by constructing user profiles based on modified collaborative filtering with detailed analysis of user's browsing history in one day.